The availability of on-board electronics and in-vehicle information systems has accelerated the development of more intelligent vehicles. One possibility is to automatically monitor a driver's driving performance to prevent potential risks. Although protocols to measure a driver's workload have been developed by both government agencies and the automobile industry, they have been criticized as being too costly and difficult to obtain. In addition, existing uniform heuristics for driving risk preventions do not account for changes in individual driving environments. Hence, technologies for understanding a driver's frustrations to prevent potential driving risks has been listed by many international automobile companies as one of the key research areas for realizing intelligent transportation systems.
Additionally, there is a need to monitor not only a driver's activity (e.g. driver inattention) but also to monitor the driver's activity with respect to certain conditions, which may be external to the vehicle or may occur within the vehicle. For example, a driver may be approaching a red light or the driver may be stopped at a red light and is looking at his cell phone or other distractions instead of being attentive to the traffic light.